{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### ❇️ Matplotlib: Inset Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's define quantities to be plotted\n",
    "x = np.linspace(0, 10)\n",
    "y = np.sin(x)\n",
    "z = np.cos(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_main = plt.subplots()\n",
    "\n",
    "# add_axis takes a parametr rect: [left, bottom, width, height], dims of the new Axes\n",
    "# All quantites are in fraction of figure height and width\n",
    "ax_inset = fig.add_axes(rect=[0.18, 0.18, 0.2, 0.2])\n",
    "\n",
    "ax_main.plot(x, y, color='red')\n",
    "ax_main.set_title('sin(x)')\n",
    "\n",
    "ax_inset.plot(x, z, color='green')\n",
    "ax_inset.set_title('cos(x)')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### ❇️ Hope you enjoyed reading!! 📖 \n",
    "##### ❇️ follow → @akshay_pachaar  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "env_twitter",
   "language": "python",
   "name": "env_twitter"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
